---
title: "Dashboard"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source: embed
---

```{r setup, include=FALSE}
library(flexdashboard)
```


```{r}
library(tidyverse)
library(httr)
library(jsonlite)
library(p8105.datasets)
library(plotly)
library(lubridate)
```

```{r}
data(rest_inspec)

#scatterplot for different longtitude and lat for grade
nyc_inspection = rest_inspec |>
  drop_na() |>
  select(boro, cuisine_description, inspection_date, score, grade, street, zipcode) |>
  mutate(
    inspection_year = as.factor(year(as.Date(inspection_date))),
    grade = as.factor(grade),
    cuisine_description = case_when(
      cuisine_description == "Latin (Cuban, Dominican, Puerto Rican, South & Central American)" ~ "Latin",
      TRUE ~ cuisine_description  # Leave other values as they are
    )
  )
```


Column {data-width=650}
-----------------------------------------------------------------------

### Chart A

```{r}
nyc_inspection|>filter(boro=="MANHATTAN")|>
  plot_ly(x = ~street, y = ~score, 
                        type = "scatter", mode = "markers", 
                        color = ~inspection_year,  colors = "viridis", alpha = 0.5)|>
  layout(
    title = "Inspection Scores by different street and year in Manhattan",
    xaxis = list(title = "Street"),
    yaxis = list(title = "Score"),
    legend = list(title = list(text = "year"))
  )
```


Column {data-width=350}
-----------------------------------------------------------------------

### Chart B

```{r}
nyc_inspection |>
  group_by(cuisine_description) |>
  summarise(count = n(), .groups = "drop") |>
  arrange(desc(count)) |>
  slice_head(n = 10) |>  # Select top 10 cuisines
  inner_join(nyc_inspection, by = "cuisine_description") |>  # Filter original data for top 10 cuisines
  group_by(cuisine_description, grade) |>
  summarise(grade_level_count = n()) |>
  plot_ly(
    x = ~cuisine_description, 
    y = ~grade_level_count, 
    color = ~grade, 
    type = "bar", 
    colors = "viridis"
  ) |>
  layout(
    title = "Grade Level Counts by Top 10 Cuisine Types",
    xaxis = list(title = "Cuisine Type", tickangle = 60),
    yaxis = list(title = "Grade Level Count")
  )

```

### Chart C

```{r}
#scores for top 15 cuisine
nyc_inspection |>
  group_by(cuisine_description) |>
  summarise(count = n(), .groups = "drop") |>
  arrange(desc(count)) |>
  slice_head(n = 15) |>  # Select the top 15 cuisines
  inner_join(nyc_inspection, by = "cuisine_description") |>
  plot_ly(
    x = ~cuisine_description, 
    y = ~score, 
    color = ~cuisine_description, 
    type = 'box', 
    colors = "viridis"
  ) |>
  layout(
    title = "Inspection Scores distribution by Cuisine Type",
    xaxis = list(title = "Cuisine Type", tickangle = 90),
    yaxis = list(title = "Score")
  )
```